A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
Missing data is a widespread problem that can affect the ability to use data to construct effective prediction systems. We investigate a common machine learning technique that can...
Qinbao Song, Martin J. Shepperd, Xiangru Chen, Jun...
Learning and reasoning from multiple documents requires students to employ the skills of sourcing (i.e., attending to and citing sources) and information integration (i.e., making ...
Mary Anne Britt, Peter M. Wiemer-Hastings, Aaron A...
We propose a new Bayesian approach to object-based image retrieval with relevance feedback. Although estimating the object posterior probability density from few examples seems in...
Derek Hoiem, Rahul Sukthankar, Henry Schneiderman,...
This paper proposes a new framework for image segmentation based on the integration of MRFs and deformable models using graphical models. We first construct a graphical model to r...